The Meteosat Third Generation (MTG) Programme is the next generation of European geostationary meteorological systems. The first MTG satellite, which is scheduled for launch at the end of 2018/early 2019, will host two imaging instruments: the Flexible Combined Imager (FCI) and the Lightning Imager. The FCI will continue the operation of the SEVIRI imager on the current Meteosat Second Generation satellites (MSG), but with an improved spatial, temporal and spectral resolution, not dissimilar to GOES-R (of NASA/NOAA). The transition from spinner to 3-axis stabilised platform, a 2-axis tapered scan pattern with overlaps between adjacent scan swaths, and the more stringent geometric, radiometric and timeliness requirements, make the rectification process for MTG FCI more challenging than for MSG SEVIRI. The effect of non-uniform sampling in the image rectification process was analysed in an earlier paper. The use of classical interpolation methods, such as truncated Shannon interpolation or cubic convolution interpolation, was shown to cause significant errors when applied to non-uniform samples. Moreover, cubic splines and Lagrange interpolation were selected as candidate resampling algorithms for the FCI rectification that can cope with irregularities in the sampling acquisition process. This paper extends the study for the two-dimensional case focusing on practical 2D interpolation methods and its feasibility for an operational implementation. Candidate kernels are described and assessed with respect to MTG requirements. The operational constraints of the Level 1 processor have been considered to develop an early image rectification prototype, including the impact of the potential curvature of the FCI scan swaths. The implementation follows a swath-based approach, uses parallel processing to speed up computation time and allows the selection of a number of resampling functions. Due to the tight time constraints of the FCI level 1 processing chain, focus is both on accuracy and performance. The presentation will show the results of our prototype with simulated FCI L1b data.

Date Published: 23 October 2014
PDF: 11 pages
Proc. SPIE 9244, Image and Signal Processing for Remote Sensing XX, 92440D (23 October 2014); doi: 10.1117/12.2066459

Published in SPIE Proceedings Vol. 9244:
Image and Signal Processing for Remote Sensing XX
Lorenzo Bruzzone, Editor(s)